Research on Optimal Scheduling Strategy of Microgrid Considering Electric Vehicle Access
Author:
Wu Zhimin1, Zou Yang1, Zheng Feng1ORCID, Liang Ning2
Affiliation:
1. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350100, China 2. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
Abstract
The random output of renewable energy and the disorderly grid connection of electric vehicles (EV) will pose challenges to the safe and stable operation of the power system. In order to ensure the reliability and symmetry of the microgrid operation, this paper proposes a microgrid optimization scheduling strategy considering the access of EVs. Firstly, in order to reduce the impact of random access to EVs on power system operation, a schedulable model of an EV cluster is constructed based on the Minkowski sum. Then, based on the wavelet neural network (WNN), the renewable energy output is predicted to reduce the influence of its output fluctuation on the operation of the power system. Considering the operation constraints of each unit in the microgrid, the network active power loss and node voltage deviation are taken as the optimization objectives, and the established microgrid model is equivalently transformed via second-order cone relaxation to improve its solution efficiency. Based on network reconfiguration and flexible load participation in demand response, the economy and reliability of system operation are improved. Finally, the feasibility and effectiveness of the proposed method are verified based on the simulation examples.
Funder
National Natural Science Foundation of China
Subject
Physics and Astronomy (miscellaneous),General Mathematics,Chemistry (miscellaneous),Computer Science (miscellaneous)
Reference18 articles.
1. Optimal Economic Dispatch of Grid-Interactive Renewable Prosumers with Hybrid Storage and Peer to Peer Energy Sharing Capabilities;Kusakana;Int. J. Electr. Electron. Eng. Telecommun.,2021 2. Hong, T., Cao, J., Zhao, W., and Lu, M. (July, January 28). Electric Vehicle Charging Scheduling Algorithm Based on Online Multi-objective Optimization. Proceedings of the 2021 International Wireless Communications and Mobile Computing (IWCMC), Harbin, China. 3. Jiang, L., Zhang, Y., Xiao, C., Zhang, J., and Li, J. (2022, January 28–30). Optimal Scheduling of Electric Vehicle Clusters Considering Uncertainty of User Demand Response. Proceedings of the 2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2), Chengdu, China. 4. Zhang, K., Gao, B., Han, Y., and Dong, Z. (2022, January 2–3). Optimization Scheduling of Electric Vehicle Charging Load Based on Improved PSO. Proceedings of the 2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC), Tumkur, India. 5. Abdalla, M.A.A., Min, W., Haroun, A.H.G., and Elhindi, M. (2021, January 2). Optimal Energy Scheduling Strategy for Smart Charging of Electric Vehicles from Grid-Connected Photovoltaic System. Proceedings of the 2021 7th International Conference on Electrical, Electronics and Information Engineering (ICEEIE), Malang, Indonesia.
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